Social Implications of Data Mining and Information Privacy: Interdisciplinary Frameworks and Solutions PDF Download
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Author: Eyob, Ephrem
Publisher: IGI Global
ISBN: 160566197X
Category : Technology & Engineering
Languages : en
Pages : 344
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Book Description
"This book serves as a critical source to emerging issues and solutions in data mining and the influence of social factors"--Provided by publisher.
Author: Eyob, Ephrem
Publisher: IGI Global
ISBN: 160566197X
Category : Technology & Engineering
Languages : en
Pages : 344
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Book Description
"This book serves as a critical source to emerging issues and solutions in data mining and the influence of social factors"--Provided by publisher.
Author: National Research Council
Publisher: National Academies Press
ISBN: 0309124883
Category : Computers
Languages : en
Pages : 377
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Book Description
All U.S. agencies with counterterrorism programs that collect or "mine" personal data-such as phone records or Web sites visited-should be required to evaluate the programs' effectiveness, lawfulness, and impacts on privacy. A framework is offered that agencies can use to evaluate such information-based programs, both classified and unclassified. The book urges Congress to re-examine existing privacy law to assess how privacy can be protected in current and future programs and recommends that any individuals harmed by violations of privacy be given a meaningful form of redress. Two specific technologies are examined: data mining and behavioral surveillance. Regarding data mining, the book concludes that although these methods have been useful in the private sector for spotting consumer fraud, they are less helpful for counterterrorism because so little is known about what patterns indicate terrorist activity. Regarding behavioral surveillance in a counterterrorist context, the book concludes that although research and development on certain aspects of this topic are warranted, there is no scientific consensus on whether these techniques are ready for operational use at all in counterterrorism.
Author: Rahman, Hakikur
Publisher: IGI Global
ISBN: 1605662313
Category : Computers
Languages : en
Pages : 378
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Book Description
"This book focuses on the data mining and knowledge management implications that lie within online government"--Provided by publisher.
Author: Kenna Jill Miskelly
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Bart Custers
Publisher: Springer Science & Business Media
ISBN: 3642304877
Category : Technology & Engineering
Languages : en
Pages : 370
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Book Description
Vast amounts of data are nowadays collected, stored and processed, in an effort to assist in making a variety of administrative and governmental decisions. These innovative steps considerably improve the speed, effectiveness and quality of decisions. Analyses are increasingly performed by data mining and profiling technologies that statistically and automatically determine patterns and trends. However, when such practices lead to unwanted or unjustified selections, they may result in unacceptable forms of discrimination. Processing vast amounts of data may lead to situations in which data controllers know many of the characteristics, behaviors and whereabouts of people. In some cases, analysts might know more about individuals than these individuals know about themselves. Judging people by their digital identities sheds a different light on our views of privacy and data protection. This book discusses discrimination and privacy issues related to data mining and profiling practices. It provides technological and regulatory solutions, to problems which arise in these innovative contexts. The book explains that common measures for mitigating privacy and discrimination, such as access controls and anonymity, fail to properly resolve privacy and discrimination concerns. Therefore, new solutions, focusing on technology design, transparency and accountability are called for and set forth.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Data mining and other information technologies cause ethical concerns when they are used to categorize and discriminate. Even though there is an intuitive connection between privacy and personal information, it is hard to conceptualize the troubling issues raised by certain data mining applications in terms of privacy. This is largely due to the emphasis that traditional privacy definitions place on the value and protection that privacy provides to the individual. A notion of "collective privacy" emphasizes the broader social importance of privacy and provides philosophical clarity to the privacy issues raised by data mining. The policy suggestions that result from acknowledging the social value of privacy could benefit many in our society and work to fortify our privacy in this information age.
Author: Jeri Freedman
Publisher: The Rosen Publishing Group, Inc
ISBN: 1508188327
Category : Young Adult Nonfiction
Languages : en
Pages : 64
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Book Description
One of the most widespread online practices today is data harvesting, the collection of users, personal data and information about their activities. Data harvesting raises significant issues about the right to privacy. This informative narrative explains what data harvesting and data mining are and how they are carried out. The importance of privacy is covered, as well as two of the most common applications of data harvesting and data mining: the selling of products and services, and the influencing of people's attitudes toward political issues. Teens learn ways that they can safeguard their data to protect their privacy.
Author: Kumaran U
Publisher:
ISBN: 9781805295266
Category :
Languages : en
Pages : 0
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Book Description
Secure Social Network Data Mining" is a comprehensive book authored by KUMARAN U, which addresses the growing concerns about privacy and security in social networks. The book explores the use of data mining techniques to extract valuable insights from social network data while protecting the privacy and security of users' personal information. The author delves into the key concepts of privacy, security, and confidentiality, and how they relate to data mining in social networks. The book highlights the importance of user privacy, anonymity, and confidentiality in data contribution and retrieval in social networks. The author examines the different techniques used for privacy preservation and data protection in social networks, including data encryption, decryption, access control, authentication, and authorization. Through the use of machine learning, artificial intelligence, and big data analytics, the book explores how data analysis can be used to identify privacy risks and threats and how to mitigate them. The author examines the impact of privacy laws and regulations on data ownership, data access, and data control in social networks. The book provides insights into user behavior and user profiling in social networks and how to protect user data during data collection, processing, storage, and transmission. The author highlights the role of cryptography in ensuring the security of social network data and the importance of user identification and verification in network security. Overall, "Secure Social Network Data Mining" offers a comprehensive examination of the challenges and opportunities associated with data mining in social networks. The book provides practical solutions for protecting user privacy and securing social network data while extracting valuable insights from social network data for research, business, and other applications
Author: Stanley Robson de Medeiros Oliveira
Publisher: Library and Archives Canada = Bibliothèque et Archives Canada
ISBN:
Category : Data mining
Languages : en
Pages : 167
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Book Description
The sharing of data is often beneficial in data mining applications. It has been proven useful to support both decision-making processes and to promote social goals. However, the sharing of data has also raised a number of ethical issues. Some such issues include those of privacy, data security, and intellectual property rights. In this thesis, we focus primarily on privacy issues in data mining, notably when data are shared before mining. Specifically, we consider some scenarios in which applications of association rule mining and data clustering require privacy safeguards. Addressing privacy preservation in such scenarios is complex. One must not only meet privacy requirements but also guarantee valid data rnining results. This status indicates the pressing need for rethinking mechanisnis to enforce privacy safeguards without losing the benefit of mining. These mechanisms can lead to new privacy control methods to convert a database into a new one in such a waY as to preserve the main features of the original database for mining. In particular, we address the problem of transforming a database to be shared into a new one that conceals private information while preserving the general patterrns and trends from the original database. To address this challening problem, we propose a unified framework for privacy-preserving data mining that ensures that the mining process will not violate privacy up to a certain degree of security. The frarnework encompasses a family of privacy-preserving data transformation rnethods, a library of algoritImis, retrieval facilities to speed up the transformation process, and a set of metrics to evaluate the effectiveness of the proposed algorithms, in terms of information loss, and to quantify how much private information has been disclosed. Our investigation concludes that privacy-preserving data mining is to some extent possible. We demonstrate empirically and tlleoretically the practicality and feasibility of achieving privacy preservation in data mining. Our experiments reveal that our framework is efféctive, meets privacy requírements. and guarantees valid data mining results while protecting sensitive information (e.g., sensitive knowIedge and individuals' privacy).
Author: Charu C. Aggarwal
Publisher: Springer Science & Business Media
ISBN: 0387709924
Category : Computers
Languages : en
Pages : 524
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Book Description
Advances in hardware technology have increased the capability to store and record personal data. This has caused concerns that personal data may be abused. This book proposes a number of techniques to perform the data mining tasks in a privacy-preserving way. This edited volume contains surveys by distinguished researchers in the privacy field. Each survey includes the key research content as well as future research directions of a particular topic in privacy. The book is designed for researchers, professors, and advanced-level students in computer science, but is also suitable for practitioners in industry.
